Say, AysegulAysegulSayFathalla, SaidSaidFathallaVahdati, SaharSaharVahdatiLehmann, JensJensLehmannAuer, SörenSörenAuer2022-03-142022-03-142020https://publica.fraunhofer.de/handle/publica/40975910.5220/0010111000640075Improvements in web technologies and artificial intelligence enable novel, more data-driven research practices for scientists. However, scientific knowledge generated from data-intensive research practices is disseminated with unstructured formats, thus hindering the scholarly communication in various respects. The traditional document-based representation of scholarly information hampers the reusability of research contributions. To address this concern, we developed the Physics Ontology (PhySci) to represent physics-related scholarly data in a machine-interpretable format. PhySci facilitates knowledge exploration, comparison, and organization of such data by representing it as knowledge graphs. It establishes a unique conceptualization to increase the visibility and accessibility to the digital content of physics publications. We present the iterative design principles by outlining a methodology for its development and applying three different evaluation approaches: data-driven and criteria-based evaluation, as well as ontology testing.enSemantic Webdomain ontologyOntology EngineeringSemantic PublishingScholarly Communicationphysics005006629conference paper